Bayesian Optimization is a method for optimizing expensive black-box functions. It is particularly useful when the function to be optimized is costly to evaluate, such as when running A/B tests in email marketing campaigns. Bayesian Optimization uses a probabilistic model to make intelligent decisions about where to sample next, thus minimizing the number of evaluations needed to find the optimal solution.